Modeling complex functions with artificial neural networks
  Single-layer neural network recap
  Introducing the multi-layer neural network architecture
  Activating a neural network via forward propagation
Classifying handwritten digits  Obtaining the MNIST dataset  Implementing a multi-layer perceptronTraining an artificial neural network  Computing the logistic cost function  Training neural networks via backpropagationDeveloping your intuition for backpropagation
Debugging neural networks with gradient checking 
Convergence in neural networks 
Other neural network architectures  Convolutional Neural Networks  Recurrent Neural NetworksA few last words about neural network implementation
Summary